Smart Cities Are Getting Smarter – And Crowd Counting Technologies Can Help

People are increasingly using smart interactive devices such as smart TVs, smart voice assistants, and smart lights in their homes to increase convenience and make everyday tasks easily doable. Similarly, the concept of smart cities is allowing the idea of developing sustainable cities to converge with a more convenient life.

Smart cities abound with smart devices like CCTV and sensors. These devices provide data, which changes the way we understand, use, and manage them. Additionally, the devices learn from this data and become smarter through Machine Learning and Deep Learning, and are connected via the Internet of Things (IoT) to develop and upgrade User Experience. An estimation from Statista predicts that “the total installed base of IoT connected devices is projected to amount to 75.44 billion worldwide by 2025, a fivefold increase in ten years.”

Smart Devices In Smart Cities

Now, the challenge is for the public and private sectors to understand crowd mobility behavior and put this into action in smart cities. In turn, this would facilitate crowd management, safety, tourism, and transportation across cities.

The idea is to deploy digital solutions to help us construct a more livable future, and the goal is to use the data we receive from these solutions to make daily lives easier.

These devices share information with business users, municipal corporations, and other governing bodies. However, smartness in cities is not achieved only by installing devices in buildings and operations. It comes by going a step further and deliberately using algorithms to use the data from the devices, with the end goal being to make better decisions for the ease of life. The real-time data from smart cities optimize organizations’ processes in three major areas:

• See the events as they happen.
• Track the demand patterns.
• Deploy low-cost solutions rapidly.

As these technology-driven urban environments progress, cities will grow smarter and become more responsive and livable.

Smart Solutions For Smart Cities

In a survey from McKinsey, private sector organizations are investing more (~60%) into smart applications than government sectors (~40%). This scenario could create endless partnership opportunities and generate huge positive returns on investments.

Smart city innovators have understood that just implementing the technologies as tools won’t do; it is just as important to continuously use the data insights they provide to improve people’s daily lives. Here’s where the developers and applications come in, with the ability to transform raw data into alerts, insights, and actions.

• Vehicle sensors help commuters to identify traffic congestion and suggest alternative routes.
• Smart health apps encourage preventive self-care to minimize the pressure on healthcare systems with data collected from smart watches
• Smart CCTV cameras can anonymously detect people to increase safety and reduce crime rates.
• Geo satellite images and camera traps can be leveraged for animal conservation and wildfire extinction.
• Crowd counting solutions allow retail industries to discover vital analytics to meet the needs of people in cities.

Crowd Counting Is The Future Of Sustainable Cities

Smart cities are, understandably, crowded. So, understanding crowd mobility behavior can help businesses develop digital solutions to manage the challenges that come with this. For example, smart counters can be attached to lampposts to count streetwalkers, which provide real-time data to people who are looking to establish businesses such as restaurants or supermarkets in cities. An accurate number of footfalls can help them measure the potential of a new venture.

Let’s simplify it with another example. A company that wants to set up a baby store in an urban area could use crowd counting models that can identify and measure people’s gender and age. For example, areas, where the count of people over 35 years old is high, could be a great spot for a shop. Even better if the count of female pedestrians is greater than males. Applications that include facial recognition can detect age and gender by working on deep learning and crowd counting models.

Crowd counting models can also count the number of vehicles on roads: As vehicles cross the sensors, they detect the flow of traffic which is then interpreted by the algorithm. These models can help cities stay eco-friendly. For example, data on the number of bicycles can help businesses know how to promote eco-friendly commuting and vehicle-counting models can help identify less polluted areas in cities.

Conclusion

The number of organizations developing smart applications for cities is increasing fast, and data and insights are key enablers for their progression. Modern-age leaders who are targeting smart cities should adapt the best crowd counting methods for the overall development of their business model. There are endless opportunities for private and public sector leaders to contribute to shaping the future of smart cities.

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